EEB321: Community Phylogenetics

The study of how evolutionary relationships among species affect the structure of communities

Lecture outline

The effect of evolutionary relatedness on the structure of communities

1. Classic theory – limiting similarity and why relatedness might matter

2. Contemporary community phylogenetics – inferring pattern from process

3. The future of phylogeny-coexistence relationships: stabilizing differences, fitness differences, and beyond

The community assembly process

Regional species pool

Habitat filter

Biotic filter

Local community

Size of available seeds (cm)

Freq

uenc

y

2.0 2.51.0 1.5 3.0

Community assembly and limiting similarity

Size of available seeds (cm)

Freq

uenc

y

2.0 2.51.0 1.5 3.0

Community assembly and limiting similarity

Many cases of and , but no

Community assembly and limiting similarity

But, how do we measure similarity?

Assumptions:• we know which traits

are important

• the important traits can be measured

• trait combinations are either known or not important

Hutchinson: the niche is an n-dimensional hypervolume

Evolutionary relationships as a proxy for species similarity

Genus 1 Genus 2

Early evidence: species to genus ratios

Elton 1946: Fewer species per genus are present locally than are regionally available

Elton et al. 1946 J of Animal EcologySimberloff 1970 Evolution

Genus 1 Genus 2 Genus 3

But, taxonomic groupings provide coarse estimates of evolutionary time

More time = more opportunity for ecological specialization

Fact: we now know that many initial classifications were actually wrong

1 mya 30 mya

• 1970s: molecular + statistical techniques improved our ability to estimate evolutionary time– expensive and time consuming

• 1990s: new computational tools to expedite the process

• Now: $5 per sequence, compared to $1000s

New phylogenetic tools

Environmental filteringCompetitive interactions

Over-dispersion Under-dispersion

Webb et al. 2002 Annu Rev Ecol Syst

Phylogenetic distance to estimate community relatedness

Because branch lengths are proportional to evolutionary time, we can sum them for the community

2 2

Phylogenetic distance = 4 units

Phylogenetic distance to estimate community relatedness

Because branch lengths are proportional to evolutionary time, we can sum them for the community

6 6

Phylogenetic distance = 12 units

Phylogenetic distance to estimate community relatedness

Because branch lengths are proportional to evolutionary time, we can sum them for the community

46

Phylogenetic distance = 14 units = 4.6 units per species

2 2

Testing phylogenetic patterns

• we need to formally test if communities are phylogenetically over- or under-dispersed

• we can use a NULL model approach, where we compare our observed data to an expected pattern if assembly was RANDOM– observed PD > expected = overdispersed– observed PD < expected = underdispersed

Null models in phylogenetic community analyses

RANDOM

Freq

uenc

yobserved value

Distribution of expectedvalues under a random pattern

The observed value is not significantly different from the null expectation

Environmental filteringCompetitive interactions

Over-dispersion Under-dispersion

Webb et al. 2002 Annu Rev Ecol Syst

Null models in phylogenetic community analyses

RANDOM

observed value

The observed value is significantly greater than the null expectation under competition

Freq

uenc

y

Environmental filteringCompetitive interactions

Over-dispersion Under-dispersion

Webb et al. 2002 Annu Rev Ecol Syst

Null models in phylogenetic community analyses

RANDOM

observed value

The observed value is significantly less than the null expectation under environmental filtering

Freq

uenc

y

Environmental filteringCompetitive interactions

Over-dispersion Under-dispersion

Phylogenetic patterns actually tend to be weak, or are inconsistent with Webb et al.’s predictions when the ecological mechanisms are known. WHY?

Problem: differences can promote or preclude coexistence via competition alone

Stabilizing differencespromote coexistence

Fitness differenceslimit coexistence

Chesson 2000; Adler et al. 2006 Ecol Lett

per c

apita

gro

wth

rate

per c

apita

gro

wth

rate

rare common rare common

Evolutionary trajectories of stabilizing (ρ) to fitness (κ) differences

Mayfield & Levine 2010 Eco Lett

Coex

isten

ce m

etric

(Δ

ρ /Δ

κ)

Phylogenetic distance

stab. diffsevolve faster

COEXISTENCE ZONE

EXCLUSIONZONE

Estimating stabilizing (ρ) to fitness (κ) differences in a competition experiment

Experimentally estimate competition coefficients and finite rates of increase, and subthose into equations that calculate stabilizing and fitness differences

20 40 60 80

0.0

0.2

0.4

0.6

0.8

1.0

Phylogenetic distance (mya)

Stab

ilizi

ng d

iffer

ence

20 40 60 80

0

10

20

30

40

Phylogenetic distance (mya)

Fitn

ess

diffe

renc

e

Our results: stabilizing and fitness differences evolve at similar rates

Close relatives: stabilizing and fitness differences minimalDistant relatives: stabilizing and fitness differences large

Coexistence is equally likely between close and distant relatives – phylogenetic overdispersion via competition

Coexistence is equally likely between close and distant relatives

Our results: stabilizing (ρ) and fitness (κ) differences evolve at similar rates

Coex

isten

ce m

etric

(Δ

ρ /Δ

κ)

Phylogenetic distance

stab. diffsevolve faster(Webb et al.)COEXISTENCE

ZONE

EXCLUSIONZONE

stab. and fit. diffsevolve at similar rates (our results)

The dynamic interplay between ecology and evolution

Evolution Ecology

We have really only scratched the surface of this question!